Visual clutter: The role of item quantity, spatial organization, and surface complexity in model and human estimates

We often consider a visual space to be cluttered if it contains a large number of items that are crowded and untidy. However, measuring clutter is complex, and clutter has been quantified using objective measures, such as mathematical models, most of which capture different aspects of clutter, and subjective measures, such as human judgments. In this study, using a well-controlled semi-realistic image database, we examined the contributions of visual factors, such as the number of items in a scene, their spatial organization, and the complexity of the surface where items are placed, to clutter by testing the predictive performance of clutter metrics and collecting human judgments of perceived clutter with respect to these factors. Our results revealed that, although all factors contribute to clutter in visual scenes, estimates by humans and metrics account only for a subset of these factors, suggesting that visual clutter is a multifaceted construct, and subjective and objective clutter should be considered together to account for several of its dimensions as a more integrative measure.